Occlusions in arteries and other portions of the cardiovascular system are often associated with various types of cardiovascular disease, such as coronary heart disease. Many of these occlusions are believed to be the source of turbulent flow and abnormal high frequency sounds approximately in the 200 to 2000 Hz, usually 300 to 1800 Hz, audio band. These sounds, generically referred to as “bruits,” are known to occur at many different time locations within a heart cycle, such as bruits that are believed to occur during diastole when the maximum pressure from the aorta surges into the arteries. Detection of bruits can provide physicians with valuable information that can be used to assess whether a patient has cardiovascular disease, such as coronary heart disease (“CHD”). Numerous techniques have attempted to detect and analyze high frequency signals from the cardiovascular sounds of a patient, some of which use averaging, neural networks, wavelet transforms, and linear prediction analysis. However, none of these conventional techniques are believed to provide a reliable probability of the likelihood that a patient has cardiovascular disease.